Amazon Personalize Runtime

{'filterArn': 'string'}

Re-ranks a list of recommended items for the given user. The first item in the list is deemed the most likely item to be of interest to the user.

See also: AWS API Documentation

Request Syntax

client.get_personalized_ranking(
    campaignArn='string',
    inputList=[
        'string',
    ],
    userId='string',
    context={
        'string': 'string'
    },
    filterArn='string'
)

type campaignArn:

string

param campaignArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the campaign to use for generating the personalized ranking.

type inputList:

list

param inputList:

[REQUIRED]

A list of items (by itemId) to rank. If an item was not included in the training dataset, the item is appended to the end of the reranked list. The maximum is 500.

• (string) --

type userId:

string

param userId:

[REQUIRED]

The user for which you want the campaign to provide a personalized ranking.

type context:

dict

param context:

The contextual metadata to use when getting recommendations. Contextual metadata includes any interaction information that might be relevant when getting a user's recommendations, such as the user's current location or device type.

• (string) --

  • (string) --

type filterArn:

string

param filterArn:

The Amazon Resource Name (ARN) of a filter you created to include or exclude items from recommendations for a given user.

rtype:

dict

returns:

Response Syntax

{
    'personalizedRanking': [
        {
            'itemId': 'string',
            'score': 123.0
        },
    ]
}

Response Structure

• (dict) --

  • personalizedRanking (list) --

    A list of items in order of most likely interest to the user. The maximum is 500.

    • (dict) --

      An object that identifies an item.

      The and APIs return a list of ``PredictedItem``s.

      • itemId (string) --

        The recommended item ID.

      • score (float) --

        A numeric representation of the model's certainty that the item will be the next user selection. For more information on scoring logic, see how-scores-work.